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 Deploying TensorFlow Models to a Web Application: Using Flask API, TensorFlowJS, and TensorFlow Serving

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Deploying TensorFlow Models to a Web Application: Using  Flask API, TensorFlowJS, and TensorFlow Serving Empty
MensajeTema: Deploying TensorFlow Models to a Web Application: Using Flask API, TensorFlowJS, and TensorFlow Serving   Deploying TensorFlow Models to a Web Application: Using  Flask API, TensorFlowJS, and TensorFlow Serving EmptyVie Nov 20, 2020 7:23 am

Deploying TensorFlow Models to a Web Application: Using  Flask API, TensorFlowJS, and TensorFlow Serving 4c49b44db35c104992bf343555abb083

Deploying TensorFlow Models to a Web Application: Using Flask API, TensorFlowJS, and TensorFlow Serving
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 38M | 699 MB
Genre: eLearning | Language: English

Implement machine learning to realize the power of AI algorithms. Developers and companies often struggle to deploy machine learning models efficiently. One of the main reasons for this is a lack of proper process set up and execution. After getting feedback and comments from his YouTube subscribers, Vikraman has created a system of step-by-step instructions for the process.
Using TensorFlow.js, you'll walk through the process of deploying machine learning models in web applications. You'll learn to deploy these models at scale and to work with users' existing hardware such as web cams to accomplish common machine learning tasks.

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